@inproceedings{brideau-duquette_when_2025,

title = {When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny},

author = {M. Brideau-Duquette and S. S. -P. Côté and P. Charbonneau and P. Renaud},

editor = {Itthipuripat S. and Ascoli G.A. and Li A. and Pat N. and Kuai H.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002448490&doi=10.1007%2f978-981-96-3294-7_10&partnerID=40&md5=61cb61b0534ab807a73107ddc116879d},

doi = {10.1007/978-981-96-3294-7_10},

isbn = {03029743 (ISSN); 978-981963293-0 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {15541 LNAI},

pages = {121–139},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.},

note = {Journal Abbreviation: Lect. Notes Comput. Sci.},

keywords = {Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{boukhalfi_tools_2015,

title = {Tools and techniques for real-time data acquisition and analysis in brain computer interface studies using qEEG and eye tracking in virtual reality environment},

author = {T. Boukhalfi and C. Joyal and S. Bouchard and S. M. Neveu and P. Renaud},

editor = {Zaremba M. Sasiadek J. Dolgui A.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953850845&doi=10.1016%2fj.ifacol.2015.06.056&partnerID=40&md5=5eaa3cab6df7946f02c74e4aded68eac},

doi = {10.1016/j.ifacol.2015.06.056},

year  = {2015},

date = {2015-01-01},

booktitle = {IFAC-PapersOnLine},

volume = {28},

pages = {46–51},

abstract = {In this paper, we present the pipeline of data acquisition and analysis used in the ARViPL lab at the Montreal Philippe-Pinel Institute for different studies related to forensic psychiatry in Virtual Reality (VR) environment and we discuss the different challenges that we encounter during the experiments when combining different new technologies that help researchers to better understand the underlying mechanisms of various mental health disorders. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},

note = {ISSN: 24058963 

Issue: 3},

keywords = {Acquisition, Analysis, brain computer interface, Data acquisition, Electroencephalography, eye tracking, Eye-tracking, Forensic, Forensic engineering, Heat maps, Interfaces (computer), Psychiatry, Real time, virtual reality},

pubstate = {published},

tppubtype = {inproceedings}

}